{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/depth-prediction/papers/3","list_of":"/task/depth-prediction","task":"Depth Prediction","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":3,"pages_in_order":5,"rows_per_page":100,"rows":[201,300],"of":422,"counts":{"archive_papers_tagged":422,"with_a_code_link":203,"where_syntology_ran_a_sample":60,"not_listed_spam_title":0,"listed":422,"listed_where_code_ran":60,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":52,"every_run_a_failure_of_syntologys_instrument":8,"listed_with_a_run_with_no_instrument_failure":52,"listed_every_run_a_failure_of_syntologys_instrument":8,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/depth-prediction","prev":"/task/depth-prediction/papers/2","next":"/task/depth-prediction/papers/4","papers":[{"url":"/paper/cad2rl-real-single-image-flight-without-a","slug":"cad2rl-real-single-image-flight-without-a","title":"CAD2RL: Real Single-Image Flight without a Single Real Image","date":"2016-11-13","arxiv_id":"1611.04201","repositories_listed":1,"syntology":null},{"url":"/paper/learning-to-navigate-in-complex-environments","slug":"learning-to-navigate-in-complex-environments","title":"Learning to Navigate in Complex Environments","date":"2016-11-11","arxiv_id":"1611.03673","repositories_listed":1,"syntology":null},{"url":"/paper/unified-depth-prediction-and-intrinsic-image","slug":"unified-depth-prediction-and-intrinsic-image","title":"Unified Depth Prediction and Intrinsic Image Decomposition from a Single Image via Joint Convolutional Neural Fields","date":"2016-03-21","arxiv_id":"1603.06359","repositories_listed":1,"syntology":null},{"url":null,"slug":"beyond-appearance-geometric-cues-for-robust","title":"Beyond Appearance: Geometric Cues for Robust Video Instance Segmentation","date":"2025-07-08","arxiv_id":"2507.05948","repositories_listed":0,"syntology":null},{"url":null,"slug":"roboscape-physics-informed-embodied-world","title":"RoboScape: Physics-informed Embodied World Model","date":"2025-06-29","arxiv_id":"2506.23135","repositories_listed":0,"syntology":null},{"url":null,"slug":"racalnet-radar-calibration-network-for-sparse","title":"RaCalNet: Radar Calibration Network for Sparse-Supervised Metric Depth Estimation","date":"2025-06-18","arxiv_id":"2506.15560","repositories_listed":0,"syntology":null},{"url":null,"slug":"difuse-net-rgb-and-dual-pixel-depth","title":"DiFuse-Net: RGB and Dual-Pixel Depth Estimation using Window Bi-directional Parallax Attention and Cross-modal Transfer Learning","date":"2025-06-17","arxiv_id":"2506.14709","repositories_listed":0,"syntology":null},{"url":null,"slug":"voyager-long-range-and-world-consistent-video","title":"Voyager: Long-Range and World-Consistent Video Diffusion for Explorable 3D Scene Generation","date":"2025-06-04","arxiv_id":"2506.04225","repositories_listed":0,"syntology":null},{"url":null,"slug":"depth-anything-with-any-prior","title":"Depth Anything with Any Prior","date":"2025-05-15","arxiv_id":"2505.10565","repositories_listed":0,"syntology":null},{"url":null,"slug":"monocop-chain-of-prediction-for-monocular-3d","title":"MonoCoP: Chain-of-Prediction for Monocular 3D Object Detection","date":"2025-05-07","arxiv_id":"2505.04594","repositories_listed":0,"syntology":null},{"url":null,"slug":"in-situ-and-non-contact-etch-depth-prediction","title":"In-situ and Non-contact Etch Depth Prediction in Plasma Etching via Machine Learning (ANN & BNN) and Digital Image Colorimetry","date":"2025-05-03","arxiv_id":"2505.03826","repositories_listed":0,"syntology":null},{"url":null,"slug":"derd-net-learning-depth-from-event-based-ray","title":"DERD-Net: Learning Depth from Event-based Ray Densities","date":"2025-04-22","arxiv_id":"2504.15863","repositories_listed":0,"syntology":null},{"url":null,"slug":"endo3r-unified-online-reconstruction-from","title":"Endo3R: Unified Online Reconstruction from Dynamic Monocular Endoscopic Video","date":"2025-04-04","arxiv_id":"2504.03198","repositories_listed":0,"syntology":null},{"url":null,"slug":"intrinsic-image-decomposition-for-robust-self","title":"Intrinsic Image Decomposition for Robust Self-supervised Monocular Depth Estimation on Reflective Surfaces","date":"2025-03-28","arxiv_id":"2503.22209","repositories_listed":0,"syntology":null},{"url":null,"slug":"tracktention-leveraging-point-tracking-to","title":"Tracktention: Leveraging Point Tracking to Attend Videos Faster and Better","date":"2025-03-25","arxiv_id":"2503.19904","repositories_listed":0,"syntology":null},{"url":null,"slug":"gaa-tso-geometry-aware-assisted-depth","title":"GAA-TSO: Geometry-Aware Assisted Depth Completion for Transparent and Specular Objects","date":"2025-03-21","arxiv_id":"2503.17106","repositories_listed":0,"syntology":null},{"url":null,"slug":"pow3r-empowering-unconstrained-3d","title":"Pow3R: Empowering Unconstrained 3D Reconstruction with Camera and Scene Priors","date":"2025-03-21","arxiv_id":"2503.17316","repositories_listed":0,"syntology":null},{"url":null,"slug":"dynamic-point-maps-a-versatile-representation","title":"Dynamic Point Maps: A Versatile Representation for Dynamic 3D Reconstruction","date":"2025-03-20","arxiv_id":"2503.16318","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-view-reconstruction-via-sfm-guided","title":"Multi-view Reconstruction via SfM-guided Monocular Depth Estimation","date":"2025-03-18","arxiv_id":"2503.14483","repositories_listed":0,"syntology":null},{"url":null,"slug":"garmentcrafter-progressive-novel-view","title":"GarmentCrafter: Progressive Novel View Synthesis for Single-View 3D Garment Reconstruction and Editing","date":"2025-03-11","arxiv_id":"2503.08678","repositories_listed":0,"syntology":null},{"url":null,"slug":"evidmtl-evidential-multi-task-learning-for","title":"EvidMTL: Evidential Multi-Task Learning for Uncertainty-Aware Semantic Surface Mapping from Monocular RGB Images","date":"2025-03-06","arxiv_id":"2503.04441","repositories_listed":0,"syntology":null},{"url":null,"slug":"lxlv2-enhanced-lidar-excluded-lean-3d-object","title":"LXLv2: Enhanced LiDAR Excluded Lean 3D Object Detection with Fusion of 4D Radar and Camera","date":"2025-02-20","arxiv_id":"2502.14503","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-inverse-laplacian-pyramid-for","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","date":"2025-02-11","arxiv_id":"2502.07289","repositories_listed":0,"syntology":null},{"url":null,"slug":"matrix3d-large-photogrammetry-model-all-in","title":"Matrix3D: Large Photogrammetry Model All-in-One","date":"2025-02-11","arxiv_id":"2502.07685","repositories_listed":0,"syntology":null},{"url":null,"slug":"fully-exploiting-vision-foundation-model-s","title":"Fully Exploiting Vision Foundation Model's Profound Prior Knowledge for Generalizable RGB-Depth Driving Scene Parsing","date":"2025-02-10","arxiv_id":"2502.06219","repositories_listed":0,"syntology":null},{"url":null,"slug":"building-rome-with-convex-optimization","title":"Building Rome with Convex Optimization","date":"2025-02-07","arxiv_id":"2502.04640","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-stable-diffusion-for-monocular","title":"Leveraging Stable Diffusion for Monocular Depth Estimation via Image Semantic Encoding","date":"2025-02-01","arxiv_id":"2502.01666","repositories_listed":0,"syntology":null},{"url":null,"slug":"uniuir-considering-underwater-image","title":"UniUIR: Considering Underwater Image Restoration as An All-in-One Learner","date":"2025-01-22","arxiv_id":"2501.12981","repositories_listed":0,"syntology":null},{"url":null,"slug":"improved-monocular-depth-prediction-using","title":"Improved Monocular Depth Prediction Using Distance Transform Over Pre-semantic Contours with Self-supervised Neural Networks","date":"2025-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"dualpm-dual-posed-canonical-point-maps-for-3d","title":"DualPM: Dual Posed-Canonical Point Maps for 3D Shape and Pose Reconstruction","date":"2024-12-05","arxiv_id":"2412.04464","repositories_listed":0,"syntology":null},{"url":null,"slug":"amodal-depth-anything-amodal-depth-estimation","title":"Amodal Depth Anything: Amodal Depth Estimation in the Wild","date":"2024-12-03","arxiv_id":"2412.02336","repositories_listed":0,"syntology":null},{"url":null,"slug":"avs-net-audio-visual-scale-net-for-self","title":"AVS-Net: Audio-Visual Scale Net for Self-supervised Monocular Metric Depth Estimation","date":"2024-12-02","arxiv_id":"2412.01637","repositories_listed":0,"syntology":null},{"url":null,"slug":"holodrive-holistic-2d-3d-multi-modal-street","title":"HoloDrive: Holistic 2D-3D Multi-Modal Street Scene Generation for Autonomous Driving","date":"2024-12-02","arxiv_id":"2412.01407","repositories_listed":0,"syntology":null},{"url":null,"slug":"monopp-metric-scaled-self-supervised","title":"MonoPP: Metric-Scaled Self-Supervised Monocular Depth Estimation by Planar-Parallax Geometry in Automotive Applications","date":"2024-11-29","arxiv_id":"2411.19717","repositories_listed":0,"syntology":null},{"url":null,"slug":"mgnicenet-unified-monocular-geometric-scene","title":"MGNiceNet: Unified Monocular Geometric Scene Understanding","date":"2024-11-18","arxiv_id":"2411.11466","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-bronchoscopy-depth-estimation","title":"Enhancing Bronchoscopy Depth Estimation through Synthetic-to-Real Domain Adaptation","date":"2024-11-07","arxiv_id":"2411.04404","repositories_listed":0,"syntology":null},{"url":null,"slug":"retrieving-snow-depth-distribution-by","title":"Retrieving snow depth distribution by downscaling ERA5 Reanalysis with ICESat-2 laser altimetry","date":"2024-10-23","arxiv_id":"2410.17934","repositories_listed":0,"syntology":null},{"url":null,"slug":"unibevfusion-unified-radar-vision-bevfusion","title":"UniBEVFusion: Unified Radar-Vision BEVFusion for 3D Object Detection","date":"2024-09-23","arxiv_id":"2409.14751","repositories_listed":0,"syntology":null},{"url":null,"slug":"boosting-generalizability-towards-zero-shot","title":"Boosting Generalizability towards Zero-Shot Cross-Dataset Single-Image Indoor Depth by Meta-Initialization","date":"2024-09-04","arxiv_id":"2409.02486","repositories_listed":0,"syntology":null},{"url":null,"slug":"madis-stereo-enhanced-stereo-matching-via","title":"MaDis-Stereo: Enhanced Stereo Matching via Distilled Masked Image Modeling","date":"2024-09-04","arxiv_id":"2409.02846","repositories_listed":0,"syntology":null},{"url":null,"slug":"catfree3d-category-agnostic-3d-object","title":"CatFree3D: Category-agnostic 3D Object Detection with Diffusion","date":"2024-08-22","arxiv_id":"2408.12747","repositories_listed":0,"syntology":null},{"url":null,"slug":"groundup-rapid-sketch-based-3d-city-massing","title":"GroundUp: Rapid Sketch-Based 3D City Massing","date":"2024-07-17","arxiv_id":"2407.12739","repositories_listed":0,"syntology":null},{"url":null,"slug":"360-in-the-wild-dataset-for-depth-prediction","title":"360 in the Wild: Dataset for Depth Prediction and View Synthesis","date":"2024-06-27","arxiv_id":"2406.18898","repositories_listed":0,"syntology":null},{"url":null,"slug":"splatter-a-video-video-gaussian","title":"Splatter a Video: Video Gaussian Representation for Versatile Processing","date":"2024-06-19","arxiv_id":"2406.13870","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-supervised-pretraining-and-finetuning","title":"Self-supervised Pretraining and Finetuning for Monocular Depth and Visual Odometry","date":"2024-06-16","arxiv_id":"2406.11019","repositories_listed":0,"syntology":null},{"url":null,"slug":"tosa-token-selective-attention-for-efficient","title":"ToSA: Token Selective Attention for Efficient Vision Transformers","date":"2024-06-13","arxiv_id":"2406.08816","repositories_listed":0,"syntology":null},{"url":null,"slug":"simplify-implant-depth-prediction-as-video","title":"Simplify Implant Depth Prediction as Video Grounding: A Texture Perceive Implant Depth Prediction Network","date":"2024-06-07","arxiv_id":"2406.04603","repositories_listed":0,"syntology":null},{"url":null,"slug":"monodetrnext-next-generation-accurate-and","title":"MonoDETRNext: Next-Generation Accurate and Efficient Monocular 3D Object Detector","date":"2024-05-24","arxiv_id":"2405.15176","repositories_listed":0,"syntology":null},{"url":null,"slug":"geocc-geometrically-enhanced-3d-occupancy","title":"GEOcc: Geometrically Enhanced 3D Occupancy Network with Implicit-Explicit Depth Fusion and Contextual Self-Supervision","date":"2024-05-17","arxiv_id":"2405.10591","repositories_listed":0,"syntology":null},{"url":null,"slug":"boosting-self-supervision-for-single-view","title":"Boosting Self-Supervision for Single-View Scene Completion via Knowledge Distillation","date":"2024-04-11","arxiv_id":"2404.07933","repositories_listed":0,"syntology":null},{"url":null,"slug":"mvd-fusion-single-view-3d-via-depth","title":"MVD-Fusion: Single-view 3D via Depth-consistent Multi-view Generation","date":"2024-04-04","arxiv_id":"2404.03656","repositories_listed":0,"syntology":null},{"url":null,"slug":"ssap-a-shape-sensitive-adversarial-patch-for","title":"SSAP: A Shape-Sensitive Adversarial Patch for Comprehensive Disruption of Monocular Depth Estimation in Autonomous Navigation Applications","date":"2024-03-18","arxiv_id":"2403.11515","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-depth-prediction-for-autonomous-driving","title":"On depth prediction for autonomous driving using self-supervised learning","date":"2024-03-10","arxiv_id":"2403.06194","repositories_listed":0,"syntology":null},{"url":null,"slug":"pyramid-feature-attention-network-for","title":"Pyramid Feature Attention Network for Monocular Depth Prediction","date":"2024-03-03","arxiv_id":"2403.01440","repositories_listed":0,"syntology":null},{"url":null,"slug":"boosting-box-supervised-instance-segmentation","title":"Boosting Box-supervised Instance Segmentation with Pseudo Depth","date":"2024-03-02","arxiv_id":"2403.01214","repositories_listed":0,"syntology":null},{"url":null,"slug":"pcdepth-pattern-based-complementary-learning","title":"PCDepth: Pattern-based Complementary Learning for Monocular Depth Estimation by Best of Both Worlds","date":"2024-02-29","arxiv_id":"2402.18925","repositories_listed":0,"syntology":null},{"url":null,"slug":"toward-accurate-camera-based-3d-object","title":"Toward Accurate Camera-based 3D Object Detection via Cascade Depth Estimation and Calibration","date":"2024-02-07","arxiv_id":"2402.04883","repositories_listed":0,"syntology":null},{"url":null,"slug":"tdc-less-direct-time-of-flight-imaging-using","title":"TDC-less Direct Time-of-Flight Imaging Using Spiking Neural Networks","date":"2024-01-19","arxiv_id":"2401.10793","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-supervised-event-based-monocular-depth","title":"Self-supervised Event-based Monocular Depth Estimation using Cross-modal Consistency","date":"2024-01-14","arxiv_id":"2401.07218","repositories_listed":0,"syntology":null},{"url":null,"slug":"nerf-vo-real-time-sparse-visual-odometry-with","title":"NeRF-VO: Real-Time Sparse Visual Odometry with Neural Radiance Fields","date":"2023-12-20","arxiv_id":"2312.13471","repositories_listed":0,"syntology":null},{"url":null,"slug":"recore-regularized-contrastive-representation","title":"ReCoRe: Regularized Contrastive Representation Learning of World Model","date":"2023-12-14","arxiv_id":"2312.09056","repositories_listed":0,"syntology":null},{"url":null,"slug":"mitigating-perspective-distortion-induced","title":"Mitigating Perspective Distortion-induced Shape Ambiguity in Image Crops","date":"2023-12-11","arxiv_id":"2312.06594","repositories_listed":0,"syntology":null},{"url":null,"slug":"wildfusion-learning-3d-aware-latent-diffusion","title":"WildFusion: Learning 3D-Aware Latent Diffusion Models in View Space","date":"2023-11-22","arxiv_id":"2311.13570","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-robust-multi-scale-representation","title":"Learning Robust Multi-Scale Representation for Neural Radiance Fields from Unposed Images","date":"2023-11-08","arxiv_id":"2311.04521","repositories_listed":0,"syntology":null},{"url":null,"slug":"joint-depth-prediction-and-semantic","title":"Joint Depth Prediction and Semantic Segmentation with Multi-View SAM","date":"2023-10-31","arxiv_id":"2311.00134","repositories_listed":0,"syntology":null},{"url":null,"slug":"dpf-nutrition-food-nutrition-estimation-via","title":"DPF-Nutrition: Food Nutrition Estimation via Depth Prediction and Fusion","date":"2023-10-18","arxiv_id":"2310.11702","repositories_listed":0,"syntology":null},{"url":null,"slug":"jointnet-extending-text-to-image-diffusion","title":"JointNet: Extending Text-to-Image Diffusion for Dense Distribution Modeling","date":"2023-10-10","arxiv_id":"2310.06347","repositories_listed":0,"syntology":null},{"url":null,"slug":"win-win-training-high-resolution-vision","title":"Win-Win: Training High-Resolution Vision Transformers from Two Windows","date":"2023-10-01","arxiv_id":"2310.00632","repositories_listed":0,"syntology":null},{"url":"/paper/large-scale-monocular-depth-estimation-in-the","slug":"large-scale-monocular-depth-estimation-in-the","title":"Large-scale Monocular Depth Estimation in the Wild","date":"2023-09-18","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"fusionformer-a-multi-sensory-fusion-in-bird-s","title":"FusionFormer: A Multi-sensory Fusion in Bird's-Eye-View and Temporal Consistent Transformer for 3D Object Detection","date":"2023-09-11","arxiv_id":"2309.05257","repositories_listed":0,"syntology":null},{"url":null,"slug":"rignet-efficient-repetitive-image-guided","title":"RigNet++: Semantic Assisted Repetitive Image Guided Network for Depth Completion","date":"2023-09-01","arxiv_id":"2309.00655","repositories_listed":0,"syntology":null},{"url":null,"slug":"r3d3-dense-3d-reconstruction-of-dynamic","title":"R3D3: Dense 3D Reconstruction of Dynamic Scenes from Multiple Cameras","date":"2023-08-28","arxiv_id":"2308.14713","repositories_listed":0,"syntology":null},{"url":null,"slug":"diffusion-augmented-depth-prediction-with","title":"Diffusion-Augmented Depth Prediction with Sparse Annotations","date":"2023-08-04","arxiv_id":"2308.02283","repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-self-supervised-extrinsic-self","title":"Robust Self-Supervised Extrinsic Self-Calibration","date":"2023-08-04","arxiv_id":"2308.02153","repositories_listed":0,"syntology":null},{"url":null,"slug":"rapid-flood-inundation-forecast-using-fourier","title":"Rapid Flood Inundation Forecast Using Fourier Neural Operator","date":"2023-07-29","arxiv_id":"2307.16090","repositories_listed":0,"syntology":null},{"url":null,"slug":"improved-neural-radiance-fields-using-pseudo","title":"Improved Neural Radiance Fields Using Pseudo-depth and Fusion","date":"2023-07-27","arxiv_id":"2308.03772","repositories_listed":0,"syntology":null},{"url":"/paper/mamo-leveraging-memory-and-attention-for","slug":"mamo-leveraging-memory-and-attention-for","title":"MAMo: Leveraging Memory and Attention for Monocular Video Depth Estimation","date":"2023-07-26","arxiv_id":"2307.14336","repositories_listed":0,"syntology":null},{"url":"/paper/lxl-lidar-exclusive-lean-3d-object-detection","slug":"lxl-lidar-exclusive-lean-3d-object-detection","title":"LXL: LiDAR Excluded Lean 3D Object Detection with 4D Imaging Radar and Camera Fusion","date":"2023-07-03","arxiv_id":"2307.00724","repositories_listed":0,"syntology":null},{"url":null,"slug":"gmm-delving-into-gradient-aware-and-model","title":"GMM: Delving into Gradient Aware and Model Perceive Depth Mining for Monocular 3D Detection","date":"2023-06-30","arxiv_id":"2306.17450","repositories_listed":0,"syntology":null},{"url":null,"slug":"simplemapping-real-time-visual-inertial-dense","title":"SimpleMapping: Real-Time Visual-Inertial Dense Mapping with Deep Multi-View Stereo","date":"2023-06-14","arxiv_id":"2306.08648","repositories_listed":0,"syntology":null},{"url":null,"slug":"lightweight-monocular-depth-estimation-via","title":"Lightweight Monocular Depth Estimation via Token-Sharing Transformer","date":"2023-06-09","arxiv_id":"2306.05682","repositories_listed":0,"syntology":null},{"url":null,"slug":"gated-stereo-joint-depth-estimation-from-1","title":"Gated Stereo: Joint Depth Estimation from Gated and Wide-Baseline Active Stereo Cues","date":"2023-05-22","arxiv_id":"2305.12955","repositories_listed":0,"syntology":null},{"url":null,"slug":"meta-optimization-for-higher-model","title":"Meta-Optimization for Higher Model Generalizability in Single-Image Depth Prediction","date":"2023-05-12","arxiv_id":"2305.07269","repositories_listed":0,"syntology":null},{"url":null,"slug":"high-resolution-synthetic-rgb-d-datasets-for","title":"High-Resolution Synthetic RGB-D Datasets for Monocular Depth Estimation","date":"2023-05-02","arxiv_id":"2305.01732","repositories_listed":0,"syntology":null},{"url":"/paper/neural-pbir-reconstruction-of-shape-material","slug":"neural-pbir-reconstruction-of-shape-material","title":"Neural-PBIR Reconstruction of Shape, Material, and Illumination","date":"2023-04-26","arxiv_id":"2304.13445","repositories_listed":0,"syntology":null},{"url":null,"slug":"fsnet-redesign-self-supervised-monodepth-for","title":"FSNet: Redesign Self-Supervised MonoDepth for Full-Scale Depth Prediction for Autonomous Driving","date":"2023-04-21","arxiv_id":"2304.10719","repositories_listed":0,"syntology":null},{"url":null,"slug":"single-image-depth-prediction-made-better-a","title":"Single Image Depth Prediction Made Better: A Multivariate Gaussian Take","date":"2023-03-31","arxiv_id":"2303.18164","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-dimensional-refined-learning-for-real","title":"Cross-Dimensional Refined Learning for Real-Time 3D Visual Perception from Monocular Video","date":"2023-03-16","arxiv_id":"2303.09248","repositories_listed":0,"syntology":null},{"url":null,"slug":"one-scalar-is-all-you-need-absolute-depth","title":"Do More With What You Have: Transferring Depth-Scale from Labeled to Unlabeled Domains","date":"2023-03-14","arxiv_id":"2303.07662","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-domain-generalization-for-multi-view","title":"Towards Domain Generalization for Multi-view 3D Object Detection in Bird-Eye-View","date":"2023-03-03","arxiv_id":"2303.01686","repositories_listed":0,"syntology":null},{"url":null,"slug":"aparate-adaptive-adversarial-patch-for-cnn","title":"APARATE: Adaptive Adversarial Patch for CNN-based Monocular Depth Estimation for Autonomous Navigation","date":"2023-03-02","arxiv_id":"2303.01351","repositories_listed":0,"syntology":null},{"url":null,"slug":"stdepthformer-predicting-spatio-temporal","title":"STDepthFormer: Predicting Spatio-temporal Depth from Video with a Self-supervised Transformer Model","date":"2023-03-02","arxiv_id":"2303.01196","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-evaluation-of-deep-learning-models-for","title":"An evaluation of deep learning models for predicting water depth evolution in urban floods","date":"2023-02-20","arxiv_id":"2302.10062","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-task-self-supervised-learning-for-image","title":"Multi-Task Self-Supervised Learning for Image Segmentation Task","date":"2023-02-05","arxiv_id":"2302.02483","repositories_listed":0,"syntology":null},{"url":null,"slug":"scenescape-text-driven-consistent-scene-1","title":"SceneScape: Text-Driven Consistent Scene Generation","date":"2023-02-02","arxiv_id":"2302.01133","repositories_listed":0,"syntology":null},{"url":null,"slug":"structure-flow-guided-network-for-real-depth","title":"Structure Flow-Guided Network for Real Depth Super-Resolution","date":"2023-01-31","arxiv_id":"2301.13416","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-the-third-dimension-in-contrastive","title":"Leveraging the Third Dimension in Contrastive Learning","date":"2023-01-27","arxiv_id":"2301.11790","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-planar-parallax-for-monocular-depth","title":"Deep Planar Parallax for Monocular Depth Estimation","date":"2023-01-09","arxiv_id":"2301.03178","repositories_listed":0,"syntology":null},{"url":null,"slug":"consistent-depth-prediction-for-transparent","title":"Consistent Depth Prediction for Transparent Object Reconstruction from RGB-D Camera","date":"2023-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"guiding-local-feature-matching-with-surface","title":"Guiding Local Feature Matching with Surface Curvature","date":"2023-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null}],"record_sha256":"2d36917ba096299bf49e74daaabf54f496b1479412fb9696cfe06285083dabfe","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}